Enrich your Elasticsearch documents within Elasticsearch
Blog post from Elastic
David Pilato's blog post delves into the process of enriching Elasticsearch documents by performing "joins at index time" using the Elasticsearch Enrich Processor and ingest pipelines. The post is the first of a three-part series exploring various methods within the Elastic ecosystem, with future installments focusing on Logstash and Elastic Agent/Beats. Pilato illustrates the process through an eCommerce example, highlighting the use of Kibana sample datasets and VIP customer data to demonstrate the enrichment of logs. The blog post describes creating and executing an enrich policy, simulating an ingest pipeline, and reindexing data to include enriched fields like customer names and VIP status. Additionally, Pilato touches on the use of runtime fields for search-time enrichment, noting the trade-offs between flexibility and search speed. He emphasizes that while runtime fields offer certain advantages, reindexing remains the preferred approach for larger datasets. The post concludes with a disclaimer that the release and timing of any features or functionality discussed are at Elastic's discretion.
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